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Data Analysis Courses

Data analysis courses cover processing, summarizing, modelling, and evaluation of data with the goal of answering questions, testing hypotheses, informing decision-making, and disproving theories. A Data Analyst usually handles this.

Managing Data Analysis

Managing Data Analysis is Course 3 of 5 in the Executive Data Science Specialization program, offered by the John Hopkins University. This 1-week course lasts about 6 hours, taught in English Subtitles are available in English and Japanese. This course which leaves out the technicalities, is focused on the process of data analysis, and its management. Participants will learn to describe basic data analysis iteration, differentiate between various types of data pulls; explore datasets to determine if data is appropriate for a project; use statistical findings to create convincing data analysis presentations; and identify different types of questions and translate them to specific datasets. Skills to be gained are in Data Analysis, Communication, Interpretation, and Exploratory Data Analysis.

Introduction to Data Analysis Using Excel

Introduction to Data Analysis Using Excel is course 1 of 5 in the Business Statistics and Analysis Specialization program, offered by the Rice University. The 4-week course taught in English lasts for about 20 hours, with subtitles in English, Spanish and Arabic. One of the most powerful tools in data analysis is the use of excel. Whether you’re new or used to Excel on a general level, this introductory course would be beneficial in moving you from basic operations like reading data into excel, organization and manipulation of data, to advanced functionality. Modules cover an introduction to spreadsheets and their functions, filtering, pivot tables, charts, and advanced graphing and charts. Access to Windows version of Microsoft Excel 2010 or later, is mandatory. Skills will be gained in Lookup Table, Data Analysis, Microsoft Excel, and Pivot Table.

Mastering Data Analysis in Excel

Mastering Data Analysis in Excel is course 2 of 5 in the Excel to MySQL: Analytic Techniques for Business Specialization program, offered by Duke University. Instructions are given in English for approximately 21 hours. Focus is on math- data-analysis concepts and methods in particular- and intermediate-to-advanced Excel functionality isn’t covered. Participants will learn needed theoretical and practical values used in business data analysis methods based off binary classification, information theory and entropy measures, and linear regression, all with Excel. Participants will be prepared to design and realistic predictive models based on data. Skills will be gained in Binary Classification, Data Analysis, Microsoft Excel, and Linear Regression.

Data Management and Visualization

Data Management and Visualization is course 1 of 5 in the Data Analysis and Interpretation Specialization program, offered by Wesleyan University. Taught in English for 16 hours, this course has subtitles in English and Korean. Learn what data is, and questions that can be answered via knowledge of data. Participants will also learn to develop research questions, describe variables and relationships, calculate basic statistics, as well as clear result presentation, all based on existing data. Progress will be shared with others to get feedback, and also learn what approach they use in answering questions. By the end, one would be able to utilize either SAS or Python in management and visualization of data, as well as deal with missing data. Gain skills in SAS Language, Data Analysis, Python Programming, and Data Management.

Data Analysis Tools

Data Analysis Tools is course 2 of 5 in the Data Analysis and Interpretation Specialization program, offered by Wesleyan University. Taught in English via online readings, videos and quizzes, this course lasts for about 14 hours. Participants will be required to choose one of two of the most powerful statistical software packages, SAS or Python, which will be used in exploring Chi-Square, ANOVA, and Pearson correlation analysis. Learn to develop and test hypotheses about data, statistical tests, as well as principles and strategies used to determine the one most appropriate when you need to answer a question. Gain skills in Chi-Squared (Chi-2) Distribution, Data Analysis, Statistical Hypothesis Testing, and Analysis Of Variance (ANOVA).

Data Analysis with Python

Data Analysis With Python is offered by IBM as a part of multiple programs, Applied Data Science Specialization, and IBM Data Science Professional Certificate. Instructions are given in English with subtitles in Arabic, Vietnamese, Korean, Turkish, and English. Python is the software package in use for this course, and would involve use of Pandas, and Scikit-learn which are open source data-analysis libraries that can be used to work with sample dataset. Participants will move from the simple basics of Python to different data exploration including data preparation for analysis, simple statistical analysis performance, creation of data visualizations, and future trends prediction. Gain skills in Predictive Modelling, Python Programming, Data Analysis, Data Visualization (DataViz), and Model Selection.

Exploratory Data Analysis

Exploratory Data Analysis is offered by the John Hopkins University and forms part of multiple programs, Data Science Specialization, and Data Science: Foundations using R Specialization. This course would last approximately 56 hours, all taught in English, with subtitles in Korean, Simplified Chinese, Vietnamese and English. In summarizing data, certain techniques have to be applied before the start of formal modelling, so as to aid in development of complex statistical models. These exploratory techniques also aid in elimination of potential hypotheses about the world. Participants would also learn plotting systems in R, some basic principles in data graphics construction, as well as common multivariate statistical methods used in high-dimensional data visualization. Gain skills in Cluster Analysis, Ggplot2, R Programming, and Exploratory Data Analysis.

Computational Thinking for Problem Solving

Computational Thinking for Problem Solving is a 4-week beginner course offered by the University of Pennsylvania. The 17-hour course focuses on computational thinking as a tool for finding solutions to a number of problems, and is recommended for everyone. Participants will learn about the standpoints of computational thinking, development and analysis of algorithms by computer scientists, fundamental operations of a modern computer, as well as use of Python programming language as a practical problem-solving medium. This course would allow for interaction within a community of analytical thinkers, to make real-world, social impact. Skills will be gained in Simple Algorithm, Python Programming, Problem Solving, and Computation.

Foundations for Big Data Analysis with SQL

Foundations for Big Data Analysis with SQL is course 1 of 3 in Modern Big Data Analysis with SQL Specialization program offered by Cloudera. This course is taught in English for approximately 12 hours, and the focus is on use of common querying language, SQL for big data. Participants would be required to download and install a virtual machine and the software on which to run it, as an exercise environment. Learn data, characteristics of big data, and exploration of databases and tables on the platform. Also learn differences between operational and analytics databases, how to effectively choose database system, and recognize features of SQL dialects utilized in big data for storage and analysis. Skills will be gained in Database (DBMS), Data Warehousing, Data Analysis, Big Data, and SQL.

Big Data Analysis with Scala and Spark

Big Data Analysis with Scala and Spark is course 4 of 5 in the Functional Programming in Scala Specialization program, offered by École Polytechnique Fédérale de Lausanne. Instructions are passed in English for approximately 28 hours in total.  Participants should have at least one year programming experience. Proficiency with Java or C# is ideal, others such as C/C++, Python, Javascript or Ruby, are sufficient. This course utilizes practical examples in Scala and Spark to show effective use of distribution-related issues in improved performance. Participants will learn the difference between Spark and other familiar programming models; how to read data from persistent storage and load into Apache Spark; how to express algorithms using a functional style; and avoid shuffles and recomputation in Spark. Gain skills in Scala Programming, Big Data, Apache Spark, and SQL.

Data Analysis and Reporting in SAS Visual Analytics

Data Analysis and Reporting in SAS Visual Analytics is course 2 of 5 in the SAS Visual Business Analytics Professional Certificate offered by SAS. The 2-week course is taught in English for approximately 8 hours. This concise course utilizes videos, online readings, and quizzes to focus on data modification via SAS Visual Analytics on SAS Viya, as well how to perform data discovery and analysis, and create interactive reports for a business scenario.

High Dimensional Data Analysis

High Dimensional Data Analysis is a Data Analysis & Statistics course offered by Havard University. This 4-week advanced course taught in English, only requires an effort of 2-4 hours weekly. Prerequisites include knowledge of basic programming, intro to statistics, or intro to linear algebra. Focus would be on techniques widely used in high-dimensional data analysis. These include mathematical distance, factor analysis, heatmaps, dimension reduction, multiple dimensional scaling plots, clustering, singular value decomposition and principal component analysis, dealing with batch effects, and a final introduction on basic machine learning concepts and how best to apply them. People interested in data analysis and interpretation will most benefit from this course.

Data Analysis Essentials

Data Analysis Essentials is a Business & Management Course offered by the Imperial College Business School, London. Taught in English for 6 weeks with 4-6 hours weekly effort, this introductory course forms part of a professional certificate, PreMBA Essentials for Professionals. The only prerequisite for this course is high school/ secondary school maths. This course serves as a preparation for your MBA, equipping you with needed data analysis skills for success. The fundamentals of presenting and summarising data, decision making, data-based decision making, and modelling for decision making, will be covered.

Data Analysis in Social Science—Assessing Your Knowledge

Data Analysis in Social Science—Assessing Your Knowledge is a Data Analysis & Statistics Course offered by the Massachusetts Institute of Technology. This 4-week course is tasking, as it requires 10-14 hours weekly. It’s all worth it though as it forms part of a MicroMasters® Program, Statistics and Data Science. People interested in this course must first take and pass Data Analysis for Social Scientists, in order to take this course, and its timed exam. Learn and master skills necessary to become informed, and effectively practise data science. Gain knowledge on techniques used in describing, summarizing, and analyzing data, as well as presenting results in a truthful way; machine learning; experimental design; and data visualization. Then, get assessed on these skills.

Data Analysis: A Practical Introduction for Absolute Beginners

Data Analysis: A Practical Introduction for Absolute Beginners is a Data Analysis & Statistics Course offered by Microsoft. Instructions are given in English for 6 weeks, with 2-4 hours weekly. The only prerequisite for this introductory course is basic excel proficiency. Learn what data is, then gain knowledge of introductory level data and mathematical concepts, work with data, apply summary statistics to analyze data and understand them, and apply analytics methods to different scenarios. Generally, learn who a data analyst is, their toolkit including data storytelling, skills needed, and different career paths available.

Business and Data Analysis Skills

Business and Data Analysis Skills is a Business & Management Course offered by Fullbridge. This course forms part of a XSeries Program, Career Development:Skills for Success, and is taught in English for 4 weeks with 1-2 hours effort per week. The goal is to learn important skills in business management, and tools and methods required to analyze data and present results. This career development course would also open you up to the world of Microsoft Excel which is not just an analytical tool, but also a communication tool. Practical application of gained knowledge is a part of this course, to ensure complete understanding that will prove useful in the growth of your organization by virtue of data-driven decisions.

Data Analysis for Decision Making

Data Analysis for Decision Making is a Business & Management Course offered by The University of Maryland. It forms part of an Associated Program, MBA Core Curriculum, and is a 7-week course, requiring effort of 8-10 hours weekly. Data analysis is critical in decision-making of every organization. Learn how to use this skill in gathering business insights, and identifying market trends early, so as to move your business up and stay competitive. Learn and understand analytical tools that’ll come in handy for data visualization, separation of variables, relationship between variables, and how generation of forecasts effect the ability to predict future trends.

Applied Data Analysis: Working in Organizations and Industries

Applied Data Analysis: Working in Organizations and Industries is a Data Analysis & Statistics Course offered by Microsoft. Taught in English, this introductory-level course will last for 6 weeks, with 2-4 hours weekly. Prerequisites include basic excel proficiency, fundamental math and statistics background, and data visualization fluency. To prepare you for your role as a Data Analyst, it’s expected that you have some level of experience. This course provides hands-on practice for the role of a data analyst in varying contexts, business, education, healthcare, and government. Also explore the different career paths available in data analysis.

Digital Skills: Web Analytics

Digital Skills: Web Analytics is a Business & Management course offered by Accenture. It is taught in English for 2 weeks, with a weekly study of 2 hours. Anyone with an interest in web analytics is welcome to join this course. This course would help participants develop needed skils and techniques in the world of analytics. Learn what analytics is, and its role in business; identify challenges in obtaining data; Google Analytics and its usefulness; and also learn the different types of analytics: descriptive, diagnostic and prescriptive.

Data to Insight: An Introduction to Data Analysis and Visualisation

Data to Insight: An Introduction to Data Analysis and Visualisation is a Business & Management Course offered by The University of Auckland. Duration of this English-taught course is 8 weeks, with a 3-hour weekly study. Explore principles of statistical analysis and data visualization, in this practical introductory course. Learn to think and act like a data analyst. Tools and free software will be provided to aid in this process which helps guide decision-making. Those new, or seeking a refresher course in data analysis and data visualization have a lot to benefit. Topics such as confidence intervals, and seasonal decomposition will be covered too.

Introduction to R for Data Science

Introduction to R for Data Science is an Engineering & Maths course offered by Purdue University for 4 weeks, with 4-hour weekly study. A desktop or laptop with R platform downloaded and installed, is a key requirement for this course. Learn how to use R platform in data management, as well as use of airline data in the demonstration of concepts involved in big data analysis. It’s basically an introductory course which prepares you for more advanced learning. Participants will use vectors and its functions, manipulate data into desired formats, and also predict the future of their business.

How to Perform a Hotel Market Analysis and Valuation

How to Perform a Hotel Market Analysis and Valuation is a Business & Management course offered by Glion Institute of Higher Education. Learn in English for 2 weeks, with 6 hours weekly. This course is ideal for managers and professionals with financial and operational responsibilities. Microsoft Excel is the tool of choice, and participants must have access to it. Focus would be on market data assembling, for use in hotel market analysis. Learn tools, and gain knowledge for creating a comprehensive hotel market study via use of hotel valuation software, to understand the fundamentals of financial projections.

Making Sense of Data

Making Sense of Data in the Media is a Politics & Society course offered by The University of Sheffield. This course lasts 3 weeks, and is ideal for anyone looking to become data literate. Learn how to read and evaluate data in the media, as well as how best to decipher fake news and misleading statistics. This will be facilitated by learning data creation, as well as survey formats and their impact on outcomes. Participants will also be taught the basic principles of data analysis including correlation, causation, and margins of sampling errors. By the end, you’ll be able to design a quantitative research project, and be equipped to critique data in the media, so as to be better informed.

Programming for Everybody: Python Data Structures

Programming for Everybody: Python Data Structures is an IT & Computer Science course offered by the University of Michigan. Instructions are passed in English for 6 weeks, with 4 hours weekly study. Learners are expected to have previously taken the Programming for Everybody course, which is for anyone interested in learning computer programming. This course is the next step in learning Python, and you’re exposed to the use of core data structures of the Python programming language. Participants will gather knowledge on use of lists, dictionaries, and tuples, all within Python, to perform complex data analysis, and learn to develop programs.

Marketing Analytics

Marketing Analytics is a Business & Management course offered by Darden School of Business, University of Virginia. Learn effective marketing via management of data, as well as basics of marketing analytics in 5 weeks. Instructions are given in English, and 2 hours weekly study is recommended. Access to spreadsheet software (Excel, Google Sheets, etc.) though helpful, isn’t required. If you’re an aspiring or practicing market professional, then this course is for you. Learn how to make decisions, and justify them via knowledge of data interpretation; calculate customer lifetime value and its components; define and evaluate a brand; and design experiments to test your hypotheses, among others.

All the courses described above are free to audit, with a small fee required to get a certificate of completion. Financial aid is available to those who qualify.